Why you should be using active learning to build ML

Why you should be using active learning to build ML

Why you should be using active learning to build ML / Humanloop blog

“Data labelling is often the biggest bottleneck in machine learning — finding, managing and labelling vast quantities of data to build a sufficiently performing model can take weeks or months. Active learning lets you train machine learning models with much less labelled data. The best AI-driven companies, like Tesla, already use active learning. We think you should too.

In this post we’ll explain what active learning is, discuss tools to use it in practice, and show what we’re doing at Humanloop to make it easier for you to incorporate active learning in NLP…”

Source: humanloop.com/blog/why-you-should-be-using-active-learning